<br/>
<hr/>
<a name="tutorials"></a>
<h3>Tutorials</h3>
<ul>
<li> New tutorial <tt>$ROOTSYS/tutorials/graphics/mass_spectrum.C</tt>. It
     produces the following output:
     <center>
     <img src="mass_spectrum.gif" alt="Mass spectrum" />
     </center>
</li>
<li>New tutorial <tt>$ROOTSYS/math/goftest.C</tt> showing the example
usage of the new <tt>ROOT::Math::GoFTest</tt> class.
</li>
<li>New tutorial <tt>$ROOTSYS/math/multiDimSampling.C</tt> showing the example
usage of the new <tt>ROOT::Math::DistSampler</tt> interface for
random generation from arbitrary functions using Unuran or Foam.
</li>
<li>New tutorial <tt>$ROOTSYS/math/kdTreeBinning.C</tt> showing the example
usage of the new <tt>TKDTreeBinning</tt> class.
</li>
<li>New tutorial <tt>$ROOTSYS/fit/NumericalMinimization.C</tt> showing
a minimization example (Rosenbrock function) using the
<tt>ROOT::Math::Minimizer</tt> interface.
</li>
<li>New tutorial <tt>$ROOTSYS/fit/exampleFit3D.C</tt> showing
a simple fit example of 3D points with a 3D function.
</li>
<li>New tutorial <tt>$ROOTSYS/fit/TSVDUnfoldExample.C</tt> showing
an example of the new <tt>TSVDUnfold</tt> class.
</li>

<br>
<li>New Roostats tutorials:


<ul>
<li>New Demos that take name for file, workspace, modelconfig, and data,  then use the corresponding calculator tool.  If the file is not specified it will read an file produced from running the HistFactory tutorial example.
<ul>
  <li><tt>StandardProfileLikelihoodDemo.C</tt>: </li>
  <li><tt>StandardFeldmanCousinsDemo.C</tt>: </li>
  <li><tt>StandardBayesianMCMCDemo.C</tt>: </li>
  <li><tt>StandardBayesianNumericalDemo.C</tt>: </li>
  <li><tt>StandardProfileInspectorDemo.C</tt>: </li>
</ul>
<li>Demonstrate some new PDFs
<ul>
  <li><tt>TestNonCentral.C</tt>: demonstrates non central chi-square</li>
  <li><tt>JeffreysPriorDemo.C</tt>: demonstrates Jeffreys Prior</li>
</ul>
<li> Instructional Examples
<ul>
  <li><tt>IntervalExamples.C</tt>: Standard Gaussian with known answer using 4 techniques</li>
  <li><tt>FourBinInstructional.C</tt>: Example of a standard data-driven approach for estimating backgrounds.  A lot of discussion.</li>
  <li><tt>HybridInstructional.C</tt>: Example of protoype on/off problem with a data-driven background estimate.  A lot of discussion</li>
  <li><tt>HybridStandardForm.C</tt>: Variant on above in 'standard form'</li>
  <li><tt>MultivariateGaussianTest.C</tt>: A validation example with an N-D multivariate Gaussian </li>
</ul>
<li>Renamed the <tt>rs201_hybridcalculator.C</tt> to
<tt>HybridOriginalDemo.C</tt></li>
<li>Removed some obsolete roostats tutorials (all the <tt>rs500</tt>  types)</li>
</ul>
</ul>
<br>
